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Defender-Aware Attacking Guidance Policy for the Target–Attacker–Defender Differential Game J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-03-01 Jacob T. English; Jay P. Wilhelm
Deep reinforcement learning was used to train an agent within the framework of a Markov decision process (MDP) to pursue a target, while avoiding a defender, for the target–attacker–defender (TAD) differential game of pursuit and evasion. The aim of this work was to explore the games where the previous attacking guidance methods found in literature failed to capture the target. The reward function
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Formation Flight in Complex Environments Using an Artificial Potential Field J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-03-01 Zhihui Du; Duo Zhao; Jingping Shi; Jingchao Lu
Studied here is the problem of multiple unmanned aerial vehicles flying in formation in an environment containing many obstacles and threats. Two schemes are proposed for avoiding obstacles: formation dissolution and formation change. The improved interfered fluid dynamical system approach is used to guide the unmanned aerial vehicles to their destination safely, and an artificial potential field is
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Neural Network Approach to Crater Detection for Lunar Terrain Relative Navigation J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-25 Lena M. Downes; Ted J. Steiner; Jonathan P. How
Terrain relative navigation can improve the precision of a spacecraft’s state estimate by providing supplementary measurements to correct for drift in an inertial measurement unit. This paper presents a crater detector, LunaNet, that uses a convolutional neural network (CNN) and image processing methods to detect craters from camera imagery taken by a spacecraft’s onboard camera. These detections are
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REStRAIN: Conceptualization of Agile Process Tools Integration with Reference to the Aerospace Industry J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-23 Malik Khalfallah
This paper describes the development of a framework that integrates engineering software and agile tools based on ontologies and business rules. The aim of this integration is to help project managers specify their own rules of integration between development software and agile tools. This integration circumvents the limitations of on-the-shelf plugins that perform a very basic integration that not
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Flight Software Development, Migration, and Testing in Desktop and Embedded Environments J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-23 Mar Cols Margenet; Hanspeter Schaub; Scott Piggott
This paper investigates different strategies for end-to-end flight software development that support having both desktop and embedded environments while minimizing the existing gap between them, in order to facilitate reiteration back and forth of the flight application. For desktop prototyping, the use of Python as a user-facing language wrapping C/C++ algorithm source code is considered. The Basilisk
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Estimation of Flight State with a Collision Alert Radar J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-21 Jerom Maas; Ronald van Gent; Jacco Hoekstra
It was found that a newly developed portable collision alert radar receives reflections from the ground while flying. In this paper a method is developed that uses range and Doppler information from these reflections. This information is used to compute height and velocity information relative to the terrain, something which is not possible with existing hardware. The method was tested on a local flight
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Open GL–Open CL Solar Radiation Pressure Modeling with Time-Varying Spacecraft Geometries J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-21 Patrick Kenneally; Hanspeter Schaub; Sergei Tanygin
A method for the fast computation of spacecraft force and torque due to solar radiation pressure (SRP) is presented. A faceted model is employed that tracks which elements of a time-varying geometry are exposed to the sunlight, but sunlight reflections are not modeled. The method uses the highly parallel execution capabilities of commodity graphics processing unit (GPU) and the Open Graphics Library
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Black-Box Expectation–Maximization Algorithm for Estimating Latent States of High-Speed Vehicles J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-21 Yoon-Yeong Kim; Hyemi Kim; WonSung Lee; Han-Lim Choi; Il-Chul Moon
Tracking an object in a noisy environment is difficult, especially when unknown parameters affect the object’s behavior. In the case of a high-speed ballistic object, its trajectory is affected by changes in atmospheric conditions as well as various parameters of the object itself. To filter these latent factors of the dynamics model, this paper proposes a black-box expectation–maximization algorithm
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Relating Sensor Degradation to Vehicle Situational Awareness for Autonomous Air Vehicle Certification J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-12 Donald H. Costello; Huan Xu
Pilots use situational awareness (SA) to make appropriate aeronautical decisions. Autonomous vehicles will not have a human pilot (or operator) in the loop when off-nominal conditions present themselves, and will rely on sensors to build SA on their environment to make sound aeronautical decisions. As their sensors degrade, it is hypothesized that a point exists where the SA those decisions are based
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Satellite Components Detection from Optical Images Based on Instance Segmentation Networks J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-09 Yulang Chen; Jingmin Gao; Yang Zhang; Zheng Duan; Kebei Zhang
For satellite interactions missions such as autonomous docking, the key to successful completion of these missions is to autonomously and accurately detect targets’ information. The missions with high precision requirement need not only to obtain the categories and location of target satellite components but also to obtain the high-level information such as the corner point. In this paper, a satellite
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Multi-Unmanned-Aerial-Vehicle Wildfire Boundary Estimation Using a Semantic Segmentation Neural Network J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-08 Jeremy Castagno; Matthew Romano; Prince Kuevor; Ella Atkins
This paper presents a system to command and control a team of fixed-wing unmanned aerial vehicles (UAVs) to sense dynamic wildfire boundaries. UAV team task and trajectory planning strategies enable the team to rapidly find, rally around, and map the wildfire boundaries. A novel boundary estimation algorithm generates two-dimensional concave polygonal estimates of multiple dynamic boundaries given
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Wind Sensing and Estimation Using Small Fixed-Wing Unmanned Aerial Vehicles: A Survey J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-01 Pengzhi Tian; Haiyang Chao; Matthew Rhudy; Jason Gross; Huixuan Wu
Journal of Aerospace Information Systems, Ahead of Print.
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Deep Learning Fault Diagnosis for Spacecraft Attitude Determination and Control J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-01 Justin R. Mansell; David A. Spencer
The growing numbers, complexity, and data return of space missions are driving a need for automated fault detection and diagnosis. Traditional fault monitoring techniques possess limited ability to diagnose anomalies, requiring operators to investigate extensive amounts of telemetry to isolate root causes. An important hurdle to automating fault diagnosis for complex subsystems such as attitude determination
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Design and Evaluation of a Constraint-Based Head-Up Display for Helicopter Obstacle Avoidance J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-02-01 Daniel Friesen; Clark Borst; Marilena D. Pavel; Olaf Stroosma; Pierangelo Masarati; Max Mulder
This paper investigates the effect of employing different display design principles for human–machine interaction in helicopters. Two obstacle avoidance support displays are evaluated during low-altitude forward flight. A baseline head-up display is complemented either by a conventional advisory display or a constraint-based display inspired by ecological interface design. The latter design philosophy
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Fast Path Planning for Unmanned Aerial Vehicles by Self-Correction Based on [math]-Learning J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-01-29 Ziyang Wang; Hongbing Yang; Qingsong Wu; Jiafei Zheng
This paper addresses a path planning problem for unmanned aerial vehicles with correcting position errors through correction-point navigation, which requires a rapid response when determining the flight path. A two-layer nested iterative hybrid algorithm based on Q learning is proposed to achieve multiobjective optimization by minimizing path lengths and correction times while reducing the complexity
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Bayesian Nonparametric State-Space Model for System Identification with Distinguishable Multimodal Dynamics J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-01-27 Young-Jin Park; Soon-Seo Park; Han-Lim Choi
The goal of system identification is to learn about underlying physics dynamics behind the time-series data. To model the probabilistic and nonparametric dynamics, Gaussian process (GP) has been widely used; GP can estimate the uncertainty of prediction. Traditional GP state-space models, however, are based on the Gaussian transition model, and thus they often have difficulty in describing more complex
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Adaptive Real-Time Clustering Method for Dynamic Visual Tracking of Very Flexible Wings J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-01-20 Tigran Mkhoyan; Coen C. de Visser; Roeland De Breuker
Advancements in aircraft controller design, paired with increasingly flexible aircraft concepts, create the need for the development of novel (smart) adaptive sensing methods suitable for aeroelastic state estimation. A potentially universal and noninvasive approach is visual tracking. However, many tracking methods require manual selection of initial marker locations at the start of a tracking sequence
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Fully Bayesian Human–Machine Data Fusion for Robust Online Dynamic Target Characterization J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2021-01-02 Jeremy Muesing; Nisar Ahmed; Luke Burks; Michael Iuzzolino; Danielle Albers Szafir
This work examines the problem of fusing human operator observations with probabilistic information extracted by an automated data fusion system, in the context of dynamic multitarget track characterization for large-scale surveillance. This soft data fusion problem is challenging because human operator observation errors are difficult to calibrate a priori and in general exhibit subtle conditional
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Different Long Short-Term Memory Approaches to Enhance Prediction-Based Satellite Telemetry Compression J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-12-29 Tarek A. Mahmoud; Ahmed F. Shehab; Mohamed A. Elshafey
Motivated by the success of deep learning in recent years, prediction-based methods are used to compress satellite telemetry data. In this paper, two-stage lossless compression methods for telemetry data are demonstrated. In the first stage, different approaches of long short-term memory (LSTM) based on one-to-one, many-to-one, and many-to-many network architectures are presented. The framework of
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Journal of Aerospace Information Systems 2020 Year-End Review J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-12-23
Journal of Aerospace Information Systems, Volume 18, Issue 1, Page 1-2, January 2021.
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Database-Driven Safe Flight-Envelope Protection for Impaired Aircraft J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-11-11 Ye Zhang; Yingzhi Huang; Qiping Chu; Coen C. de Visser
In this paper, an online flight envelope protection system is developed and implemented on impaired aircraft with structural damage. The whole protection system is designed to be a closed loop of several subsystems, including system identification, damage classification, flight-envelope prediction, and fault-tolerant control. Based on the information given by damage classification, the flight envelopes
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Modeling and Validating Launch Vehicle Onboard Software Using the SPIN Model Checker J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-10-31 Ranjani Krishnan; V. R. Lalithambika
Journal of Aerospace Information Systems, Ahead of Print.
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Cessna Citation X Takeoff and Departure Trajectories Prediction in Presence of Winds J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-10-22 Georges Ghazi; Ruxandra M. Botez; Nicolas Maniette
This paper presents a method developed at the Laboratory of Applied Research in Actives Controls, Avionics, and AeroServoElasticity for calculating takeoff and departure trajectories of a Cessna Citation X business aircraft. The method consisted of integrating the aircraft equations of motion for each segment corresponding to a typical takeoff and departure profile. For this purpose, the aircraft trajectory
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Generating Certification Evidence for Autonomous Aerial Vehicles Decision-Making J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-10-22 Donald H. Costello; Huan Xu
The last 15 years have seen a large uptick in the use of unmanned aircraft. However, the current safety of flight clearances for unmanned aircraft requires a qualified operator who can make decisions and ultimately bear the responsibly for the safe operations of the vehicle. The future of aviation is unmanned, and ultimately autonomous. Yet, a clear path for certifying an autonomous vehicle to make
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Air Transportation Direct Share Time Series Forecasting: A Hybrid Model J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-10-22 Xufang Zheng; Peng Wei
In modern air transportation, the direct share is the ratio of direct passengers to total passengers on a directional origin and destination (O&D) pair. The forecasting of direct share time series on the O&D level, as part of the detailed demand forecasting, plays a fundamental role in air transportation planning and development. An accurate forecasting of the O&D direct share time series can benefit
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Heuristic Approach for Arrival Management of Aircraft in On-Demand Urban Air Mobility J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-09-19 Priyank Pradeep; Peng Wei
The arrival sequencing and scheduling problem have been formulated in the urban air mobility (UAM) context for homogeneous and mixed fleets of electric vertical takeoff and landing (EVTOL) aircraft (winged/wingless) expected to land on a vertiport. In this paper, a novel UAM airspace design concept has been proposed to separate arrival air traffic of wingless EVTOL aircraft from winged EVTOL aircraft
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Mitigation of Ground Impact Hazard for Safe Unmanned Aerial Vehicle Operations J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-09-11 Andrew Poissant; Lina Castano; Huan Xu
Autonomous operation of unmanned aerial vehicles (UAVs) requires development of technologies that allow for safer flight control and response to various flight anomalies. Software for autonomous control should allow the UAV to detect and avoid potential hazards, as well as respond to critical failures midflight without input from a human operator. This paper develops a ground impact and hazard mitigation
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ADflow: An Open-Source Computational Fluid Dynamics Solver for Aerodynamic and Multidisciplinary Optimization J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-22 Charles A. Mader; Gaetan K. W. Kenway; Anil Yildirim; Joaquim R. R. A. Martins
Computational fluid dynamics through the solution of the Navier–Stokes equations with turbulence models has become commonplace. However, simply solving these equations is not sufficient to be able to perform efficient design optimization with a flow solver in the loop. This paper discusses the recommendations for developing a flow solver that is suitable for efficient aerodynamic and multidisciplinary
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Long-Range Pose Estimation for Aerial Refueling Approaches Using Deep Neural Networks J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-25 Andrew Lee; Will Dallmann; Scott Nykl; Clark Taylor; Brett Borghetti
Automated aerial refueling (AAR) provides unique challenges for computer vision systems. Aerial refueling maneuvers require high-precision low-variance pose estimates. The performance of two stereoscopic (stereo) vision systems is quantified in ground tests specially designed to mimic AAR. In this experiment, three-dimensional (3-D) pose-estimation errors of 6 cm on a target 30 m from the current vision
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Unimpeded Taxi-Time Prediction Based on the Node–Link Model J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-25 Myeongsook Jeong; Yeonju Eun; Daekeun Jeon; Hyochoong Bang
This paper presents a new method for predicting unimpeded taxi time based on the airport node–link model through statistical analysis of the airport surface detection equipment surveillance data. The proposed method can predict taxi-out and taxi-in times for departure and arrival flights, respectively, by calculating the link travel times on a node–link model of the airport surface movement. The prediction
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Global Navigation Satellite System Fault Detection Protection Level Using Parametrized Quadratic Programming J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-25 Teng-Yao Yang; Dengfeng Sun
With the aim to benefit vertical guidance in performance-based navigation using the multiconstellation global navigation satellite systems, this research addresses the integrity of the detection and exclusion of faulty global navigation satellite system measurements with the parameterized quadratic programming (PQP) method proposed in prior research. In particular, the PQP method is integrated with
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Formal Analysis of Unmanned Aerial Vehicles Using Higher-Order-Logic Theorem Proving J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-25 Sa’ed Abed; Adnan Rashid; Osman Hasan
The continuous dynamics of unmanned aerial vehicles (UAVs) are generally modeled as a set of differential equations. Traditionally, these continuous dynamics of UAVs are analyzed using paper-and-pencil proof and computer-based testing or simulations to study the performance, stability, and various other control characteristics of the aircraft flying in the air. However, these techniques suffer from
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Flight Object Sharing Capability Using Blockchain J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-28 Duncan Thomson; Steven R. Bodie; David E. Bryson; Timothy S. Luc; Joel G. Korb
This paper describes a concept and a prototype for sharing flight information using blockchain technology. Providing all stakeholders access to complete, consistent, and up-to-date information about each flight facilitates efficient aviation operations. Existing flight information exchange methods are limited; the concept of a “flight object” that provides a complete solution for all stakeholders has
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General-Purpose Object-Oriented Framework for Vorticity-Dominated Flow Simulation J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-07-01 Martín E. Pérez Segura; Dean T. Mook; Sergio Preidikman
This paper describes the development of a computational framework for aerodynamic simulations based on the unsteady vortex lattice method under the object-oriented programming paradigm. The effort aims to fulfill the fluid-dynamics portion of the fluid–structure interaction problem in the multiphysics field. The construction and implementation of an object-oriented model is introduced along with its
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Pseudomeasurement-Aided Estimation of Angle of Attack in Mini Unmanned Aerial Vehicle J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-08-10 S. Prem; L. Sankaralingam; C. Ramprasadh
This work focuses on a novel pseudomeasurement-aided estimation scheme for angle of attack (AOA) in a mini unmanned aerial vehicle with a 1.61 m wingspan. A scale-reduced model of the same is used in a wind tunnel, and the necessary measurements are recorded. Wind-tunnel measurements are used to write down the CL and CD equations of the flight vehicle. A pseudomeasurement-aided scheme for estimation
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Cooperative Relative Navigation of Multiple Aircraft in Global Positioning System-Denied/Degraded Environments J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-07-13 Gary Ellingson; Kevin Brink; Tim McLain
This paper introduces a method for enabling multiple small unmanned aircraft to improve navigational accuracy in Global Positioning System (GPS)-denied environments by cooperatively sharing information. The method uses a multilevel framework called relative navigation and visual-inertial odometry: both of which have been used for single-vehicle GPS-denied navigation. This work modifies the relative
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Introduction to the Special Issue on Multi-agent Coordination and Control J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-07-31 David W. Casbeer; Satyanarayana G. Manyam; Rajnikant Sharma
Journal of Aerospace Information Systems, Volume 17, Issue 8, Page 370-370, August 2020.
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Failure Analysis for an Unmanned Aerial Vehicle Using Safe Path Planning J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-07-01 Chin E. Lin; Pei-Chi Shao
Unmanned aerial vehicles (UAVs) are sufficiently mature to operate in manned airspace. Failure analysis with a risk assessment is critical to aviation safety. Performance criteria are analyzed to d...
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Optimization of Shop Visit for Aeroengine Using the Proportional Hazard Model J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-07-01 Jing Cai; Xianbiao Wu; Xi Chen; Juan Xu
According to the definition given by the world airlines technical operations glossary (WATOG), an aeroengine removal is classified as a shop visit (SV) whenever the subsequent engine maintenance pe...
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Two-Phase Neural Combinatorial Optimization with Reinforcement Learning for Agile Satellite Scheduling J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-07-01 Xuexuan Zhao; Zhaokui Wang; Gangtie Zheng
The agile Earth observing satellite (AEOS) scheduling problem consists of scheduling a set of image acquisitions and selecting the start time of each acquisition, satisfying the constraints and max...
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Formal Framework for Safety, Security, and Availability of Aircraft Communication Networks J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-07-01 Rohit Dureja; Kristin Yvonne Rozier
As the costs of fuel and maintenance increase and regulations on weight and environmental impact tighten, there is an increasing push to transition onboard aircraft networks to wireless, reducing w...
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Cooperative Navigation Using Pairwise Communication with Ranging and Magnetic Anomaly Measurements J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-03 Chizhao Yang; Jared Strader; Yu Gu; Aaron Canciani; Kevin Brink
The problem of cooperative localization for a small group of unmanned aerial vehicles (UAVs) in a Global Navigation Satellite System-denied environment is addressed in this paper. The presented approach contains two sequential steps: first, an algorithm called cooperative ranging localization, formulated as an extended Kalman filter, estimates each UAV’s relative pose inside the group using intervehicle
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New Methodology for Aircraft Performance Model Identification for Flight Management System Applications J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-01 Georges Ghazi; Ruxandra Mihaela Botez; Simon Domanti
This paper presents the validation results of a study conducted at the Laboratory of Applied Research in Actives Controls, Avionics, and Aeroservoelasticity to develop a modeling technique for dete...
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Task Scheduling of Agile Satellites with Transition Time and Stereoscopic Imaging Constraints J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-01 Junhong Kim; Jaemyung Ahn; Han-Lim Choi; Doo-Hyun Cho
This paper proposes a framework for scheduling the observation and download tasks of multiple agile satellites with practical considerations such as attitude transition time, onboard data capacity,...
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An Interactive Conflict Solver for Learning Air Traffic Conflict Resolutions J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-01 Phu N. Tran; Duc-Thinh Pham; Sim Kuan Goh; Sameer Alam; Vu Duong
The increasing demand in air transportation is pushing the current air traffic management system to its limits in the airspace capacity and workload of air traffic controllers (ATCOs). ATCOs are in...
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Multiple-Hypothesis Vision-Based Landing Autonomy J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-06-01 Takuma Nakamura; Eric N. Johnson
This paper presents a novel state estimation system for unmanned aerial vehicle landing. A novel vision algorithm that detects a portion of the marker is developed, and this algorithm extends the detectable range of the vision system for any known marker. A vision-aided navigation algorithm is derived within extended Kalman particle filter and Rao–Blackwellized particle filter frameworks in addition
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Basilisk: A Flexible, Scalable and Modular Astrodynamics Simulation Framework J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-05-22 Patrick W. Kenneally; Scott Piggott; Hanspeter Schaub
The Basilisk astrodynamics framework is a spacecraft simulation tool developed with an aim of strict modular separation and decoupling of modeling concerns in regard to coupled spacecraft dynamics, environment interactions, and flight software algorithms. Modules, tasks, and task groups are the three core components that enable Basilisk’s modular architecture. These core components are described and
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Estimation of Thermal-Conductivity Coefficients in the Global Ionosphere–Thermosphere Model J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-05-11 Ankit Goel; Brandon Ponder; Aaron Ridley; Dennis S. Bernstein
This paper uses retrospective cost parameter estimation (RCPE) to estimate parameters in the global ionosphere–thermosphere model (GITM). Using GITM as an executable simulation code, RCPE estimates two thermal-conductivity coefficients along with the temperature exponent in the thermal-conductivity model. These parameter estimates are obtained by using various combinations of simulated measurements
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Cooperative Pursuit Guidance to Surround Intruder Swarms Using Collision Cones J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-05-11 Animesh Chakravarthy; Debasish Ghose
This paper addresses the problem of n unmanned aerial vehicles (UAVs) pursuing a swarm of target UAVs moving on a plane. The target UAVs are assumed to be flying together as a flock. The flock is initially modeled as a circle whose radius can be time varying, and this is subsequently generalized to arbitrarily shaped swarms that may change in size. Capture is said to occur when the n pursuing UAVs
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Modified Reliability Centered Maintenance Analysis Considering Probability of Detection J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-05-01 Sung Jin Kim; Hee-Seong Kim; Joo-Ho Choi
In the maintenance of aircraft structural parts, a routine inspection is conducted to prevent fatigue crack growth beyond the critical size during the service life. Traditionally, the inspection in...
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Single Pursuer and Two Cooperative Evaders in the Border Defense Differential Game J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-05-01 John L. Salmon; Landon C. Willey; David Casbeer; Eloy Garcia; Alexander Von Moll
An interest in border defense, surveillance, and interdiction has recently increased for a variety of reasons related to issues of illegal immigration, terrorism, drug and human trafficking, and ot...
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Velocity Measurement Improvement of Landing Radar Considering Irradiated Surface Using Neural Networks J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-05-01 Moeko Hidaka; Masaki Takahashi; Takayuki Ishida; Kazuki Kariya; Takahide Mizuno; Seisuke Fukuda
In this study, a signal-processing method for the landing radar of a lunar lander is proposed using deep learning. To perform a precise landing, measurement of the relative velocity with respect to...
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Verification and Validation of Convex Optimization Algorithms for Model Predictive Control J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-05-01 Raphael Cohen; Eric Feron; Pierre-Loïc Garoche
Advanced embedded algorithms are growing in complexity, and they are an essential contributor to the growth of autonomy in many areas. However, the promise held by these algorithms cannot be kept w...
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Blockchain Properties for Near-Planetary, Interplanetary, and Metaplanetary Space Domains J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-04-30 David Hyland-Wood; Peter Robinson; Sandra Johnson; Christopher Hare; Brett Henderson; Chris Lewicki; Roberto Saltini
Blockchain technologies have demonstrated new and interesting ways to construct terrestrial economies, including the well-known public cryptocurrencies, but also as a means to facilitate business-to-business and business-to-consumer transactions. Some have recently proposed uses for blockchains in space. This paper identifies desirable blockchain properties that could be used to construct future in-space
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Guaranteed Collision Avoidance in Multivehicle Cooperative Missions Using Speed Adjustment J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-04-30 Camilla Tabasso; Venanzio Cichella; Syed Bilal Mehdi; Thiago Marinho; Naira Hovakimyan
This paper presents a speed-adjustment method for avoiding obstacles during multivehicle missions. This method enables multiple autonomous agents to cooperatively avoid collision against popup moving obstacles while at the same time guaranteeing intervehicle safety. The collision-avoidance algorithm assumes knowledge of a nominal trajectory for the obstacle and takes into account bounded deviations
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Information-Rich Formation Tracking: A Unified Scheme of Cooperative Control and Localization J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-04-30 Arijit Sen; Mangal Kothari; Soumya Ranjan Sahoo
A group of unmanned aerial vehicles (UAVs) can efficiently obtain the information of an unknown target or location of interest. Efficacy of localization gets enhanced if UAVs form an optimal formation geometry around the target. This work presents a unified scheme of cooperative localization and tracking for a group of fixed-wing unmanned aerial vehicles. The sensors having different types and qualities
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Haptic Assistance for Helicopter Control Based on Pilot Intent Estimation J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-04-01 Giulia D’Intino; Mario Olivari; Heinrich H. Bülthoff; Lorenzo Pollini
Haptic support systems have been widely used for supporting human operators when performing a manual control task. These systems are commonly designed to track known target trajectories. However, t...
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Automated Volcano Monitoring Using Multiple Space and Ground Sensors J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-04-01 Steve A. Chien; Ashley G. Davies; Joshua Doubleday; Daniel Q. Tran; David Mclaren; Wayne Chi; Adrien Maillard
From 2004 to 2017, an effort was undertaken to integrate space-borne sensing and in situ sensing in an automated system to improve global volcano activity monitoring. This paper reviews a sensor we...
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Detecting Semantic Bugs in Autopilot Software by Classifying Anomalous Variables J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-04-01 Hu Huang; Samuel Z. Guyer; Jason H. Rife
Like any software, manned-aircraft flight management systems and unmanned aerial system autopilots contain bugs. A large portion of bugs in autopilots are semantic bugs, where the autopilot does no...
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Assessment of Finescale Local Wind Forecasts Using Small Unmanned Aircraft Systems J. Aerosp. Inf. Syst. (IF 1.076) Pub Date : 2020-04-01 Katherine Glasheen; James Pinto; Matthias Steiner; Eric Frew
Control of small unmanned aircraft systems (sUAS) is influenced by local wind field characteristics. Small UAS missions contained within subgrid regions of current numerical weather prediction (NWP...